Comprehensive High-throughput Mapping of Cancer Genomes

癌症基因组的综合高通量作图

• 批准号: 7280617
• 负责人: Aleksandar Milosavljevic
• 金额: $ 19.19万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7280617
• 关键词: Bacterial Artificial Chromosomes; Bacterial Chromosomes; Biological; Biological Sciences; Breast Cancer Cell; Cancer cell line; Carcinoma; Cells; Chromosome abnormality; Clinical; Complex; Cytogenetics; DNA Sequence; DNA Sequence Rearrangement; Data; Detection; Development; Diagnostic; Equilibrium; Event; Genes; Genome; Genome Mappings; Genomics; Heterogeneity; Human; Informatics; Knowledge; MCF7 cell; Malignant Neoplasms; Maps; Methodology; Methods; Population; Primary Neoplasm; Principal Investigator; Prognostic Marker; Protocols documentation; Range; Recurrence; Resolution; Sampling; Scientist; Solid Neoplasm; Specimen; Structure; System; Technology; Testing; Transformed Cell Line; Woman; Work; base; cancer genome; cancer therapy; clinically significant; cost; day; dosage; genome sequencing; improved; leukemia/lymphoma; malignant breast neoplasm; mecarzole; neoplastic cell; new technology; next generation; novel; programs; sarcoma; therapeutic target; tumor; tumor progression; web-accessible

DESCRIPTION (provided by applicant): This project aims to develop comprehensive, rapid, and economical methods for detecting recurrent chromosomal aberrations in cancer. The methods will allow detection of recurrent chromosomal aberrations in hundreds of small (< 1000 cells) specimens at the Kbp level of resolution, including small deletions and aberrant joins induced by balanced rearrangements. This development project employs next-generation technologies and methodologies essential for large-scale genome sequencing and mapping .To enable analyses of resulting data by basic scientists and clinicians who are not experts in genomics, the methods will be supported by Genboree, a turnkey web- accessible informatic system developed in the context of genome mapping projects at the BCM Human Genome Sequencing Center. Recurrent rearrangements have both biological and clinical importance: 1) they have been implicated as causative events in cancer progression, 2) they can be used as highly informative diagnostic and prognostic markers, and 3) they have served as therapeutic targets. Comprehensive high-resolution mapping of genomes in multiple transformed cell lines and primary tumor samples will reveal novel biologically and clinically significant recurrent chromosomal aberrations. Recurrent chromosomal aberrations are best understood in leukemias, lymphomas, and sarcomas. However, recent evidence suggests that carcinomas also contain biologically important highly recurrent rearrangements, which we aim to discover using the proposed methods. Due to the more complex structure of rearrangements and heterogeneity of cell populations in carcinomas, recurrent rearrangements are only partially detectable using current cytogenetic methods. The study of highly rearranged genomes such as those found in breast cancer and other carcinomas will particularly benefit from an increase in resolution beyond currently available technologies. This project will develop a novel technology for identifying gene aberrations that are involved in the progression of breast cancer, the most common cancer among women, and in the progression of other solid tumors. The knowledge about specific gene aberrations gained through the application of the technology will enable development of novel highly targeted cancer therapies.

描述（由申请人提供）：本项目旨在开发全面、快速和经济的方法，用于检测癌症中复发性染色体畸变。该方法将允许在Kbp分辨率水平下检测数百个小样本（< 1000个细胞）中的复发性染色体畸变，包括由平衡重排诱导的小缺失和异常连接。该开发项目采用了大规模基因组测序和绘图所必需的下一代技术和方法，为了使非基因组学专家的基础科学家和临床医生能够分析结果数据，这些方法将得到Genboree的支持，Genboree是一个交钥匙的网络访问信息系统，是在生物技术研究所人类基因组测序中心基因组绘图项目的背景下开发的。复发性重排具有生物学和临床重要性：1）它们被认为是癌症进展中的致病事件，2）它们可以用作高度信息化的诊断和预后标志物，以及3）它们已用作治疗靶点。在多个转化细胞系和原发性肿瘤样本中对基因组进行全面的高分辨率作图，将揭示新的具有生物学和临床意义的复发性染色体畸变。复发性染色体畸变在白血病、淋巴瘤和肉瘤中最为常见。然而，最近的证据表明，癌也包含生物学上重要的高度复发性重排，我们的目标是发现使用所提出的方法。由于癌细胞群的重排结构和异质性更复杂，使用目前的细胞遗传学方法只能部分检测到复发性重排。研究高度重排的基因组，如在乳腺癌和其他癌症中发现的基因组，将特别受益于目前可用技术分辨率的提高。该项目将开发一种新技术，用于识别与乳腺癌（女性中最常见的癌症）以及其他实体瘤进展有关的基因畸变。通过该技术的应用获得的关于特定基因畸变的知识将能够开发新型高度靶向的癌症疗法。